Instructions to use Davlan/mt5_base_yor_eng_mt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Davlan/mt5_base_yor_eng_mt with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Davlan/mt5_base_yor_eng_mt") model = AutoModelForSeq2SeqLM.from_pretrained("Davlan/mt5_base_yor_eng_mt") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 932f00f18fbf78a067c3d14dc806f0fe2feabb8a906f3844ae0a655dade88726
- Size of remote file:
- 2.35 kB
- SHA256:
- 73fa46383c97e879cdce70ed7d7da99c212b106e7cd8e618e0f10f64145c0b04
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.